Discovering and Tracking Query Oriented Topical Clusters in Online Social Networks

Online Social Networks (OSNs) are comprehensive media that help individuals to be connected through social networking sites (SNS) such as Twitter, Instagram, etc. People share their interests, activities and can exchange ideas. OSNs are typically large in size and complex as those media have an enormous number of users and multi kind relationships among them. Users reveal their interests in diverse topics in OSN and mostly, users' degree of topical interest changes over time. Tracking users' interests from such SNS and grouping users having similar interests based on that becomes significant for various domains. In this paper, we pay attention to identify and track users' topical interests on Twitter over time. Next, we group users with similar degrees of interest in different clusters. We perform experiments on real datasets and got interesting results.